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    • Computational Biology

    Computational Biology Courses Online

    Explore computational biology for analyzing biological data. Learn to apply algorithms and models to study genomes, proteins, and biological systems.

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    Explore the Computational Biology Course Catalog

    • U

      University of California San Diego

      Biology Meets Programming: Bioinformatics for Beginners

      Skills you'll gain: Bioinformatics, Programming Principles, Molecular Biology, Python Programming, Computational Thinking, Biology, Algorithms, Data Structures

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of Washington

      Computational Neuroscience

      Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Mathematical Modeling, Biology, Linear Algebra, Probability & Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.1K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Genomic Data Science

      Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Molecular Biology, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Data Analysis Software, Statistical Modeling, Data Structures, Data Analysis, R Programming, Computational Thinking, Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Bioinformatics

      Skills you'll gain: Bioinformatics, Molecular Biology, Dimensionality Reduction, Unsupervised Learning, Applied Machine Learning, Data Analysis, Computational Thinking, Graph Theory, Markov Model, Biochemistry, Life Sciences, Microbiology, Statistical Analysis, Medical Science and Research, Precision Medicine, Biology, Pharmacology, Algorithms, Infectious Diseases, Data Mining

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      I

      Icahn School of Medicine at Mount Sinai

      Systems Biology and Biotechnology

      Skills you'll gain: Matlab, Bioinformatics, Quantitative Research, Unsupervised Learning, Data Synthesis, Mathematical Modeling, Molecular Biology, Data Analysis, Pharmacology, Science and Research, Network Analysis, Analytical Skills, Scientific Methods, Differential Equations, Computational Logic, Experimentation, Biochemistry, Laboratory Experience, Analysis, Biology

      4.4
      Rating, 4.4 out of 5 stars
      ·
      973 reviews

      Intermediate · Specialization · 3 - 6 Months

    • P

      Peking University

      Bioinformatics: Introduction and Methods 生物信息学: 导论与方法

      Skills you'll gain: Bioinformatics, Markov Model, Molecular Biology, Computational Thinking, Biology, Database Software, Data Analysis, Algorithms, Machine Learning Algorithms, Probability & Statistics, Data Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      279 reviews

      Mixed · Course · 3 - 6 Months

    • D

      Duke University

      Introduction to Genetics and Evolution

      Skills you'll gain: Life Sciences, Molecular Biology, Biology, Biostatistics, Bioinformatics, Environment, Laboratory Research, Taxonomy, Scientific Methods, Experimentation, Mathematical Modeling

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 3 Months

    • U

      University of Pennsylvania

      Computational Thinking for Problem Solving

      Skills you'll gain: Computational Thinking, Algorithms, Pseudocode, Python Programming, Data Structures, Computer Hardware, Computer Programming, Analysis, Debugging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Genomic Technologies

      Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Programming Principles, Computer Science, Statistical Analysis, Computational Thinking, Big Data, Software Engineering, Algorithms, Biology

      4.6
      Rating, 4.6 out of 5 stars
      ·
      4.7K reviews

      Mixed · Course · 1 - 4 Weeks

    • S

      Stanford University

      RNA Biology with Eterna

      Skills you'll gain: Molecular Biology, Bioinformatics, Biochemistry, Chemical and Biomedical Engineering, Biology, Medical Science and Research, Chemistry

      4.7
      Rating, 4.7 out of 5 stars
      ·
      120 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Bioinformatic Methods I

      Skills you'll gain: Bioinformatics, Molecular Biology, Biology, Data Analysis Software, Data Mining, Life Sciences, Analysis, Statistical Analysis, Databases

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Python for Genomic Data Science

      Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Scripting Languages, Scripting, Data Processing, Computer Programming, Data Manipulation, File Management

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.8K reviews

      Mixed · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular computational biology courses

    • Biology Meets Programming: Bioinformatics for Beginners: University of California San Diego
    • Computational Neuroscience: University of Washington
    • Genomic Data Science: Johns Hopkins University
    • Bioinformatics: University of California San Diego
    • Systems Biology and Biotechnology: Icahn School of Medicine at Mount Sinai
    • Bioinformatics: Introduction and Methods 生物信息学: 导论与方法: Peking University
    • Introduction to Genetics and Evolution: Duke University
    • Computational Thinking for Problem Solving: University of Pennsylvania
    • Introduction to Genomic Technologies: Johns Hopkins University
    • RNA Biology with Eterna: Stanford University

    Skills you can learn in Algorithms

    Graphs (22)
    Mathematical Optimization (21)
    Computer Program (20)
    Data Structure (19)
    Problem Solving (19)
    Algebra (12)
    Computer Vision (10)
    Discrete Mathematics (10)
    Graph Theory (10)
    Image Processing (10)
    Linear Algebra (10)
    Reinforcement Learning (10)

    Frequently Asked Questions about Computational Biology

    Computational Biology is a multidisciplinary approach to applying data-scientific methods, processes, or theories to the study of biological systems. The field includes foundations in Mathematics, Statistics, Chemistry, Genetics, Genomics, Computer Science, Evolution, and related disciplines.

    An example of Computational Biology is performing experiments that produce data—building sequences of molecules, for instance—and then using methods such as machine learning to analyze the data.

    When mastered, Computational Biology enables successful learners to bring drug discovery and disease prevention expertise to Biotechnology, Pharmaceuticals, and other essential fields.‎

    As Data Science roles pertaining to Biology become increasingly in-demand, learners exploring Computational Biology can find opportunities in commercial, academic, and government domains. The positions learners can look forward to include Computer and Information Research Scientist, Computational Biology Professor, Software and Instrumentation Test Engineer, Bioinformatics Scientist, and related roles.

    Some industries in which Computational Biology learners will find exciting opportunities include Medical Device and Equipment, Research and Testing, Agricultural Chemicals, Pharmaceuticals, National Institutes of Health, and more.‎

    Courses in Computational Biology offered through Coursera explore various methods for extracting data from biological experiments. Learners discover how algorithms, data structures, and other computational methods can help them analyze DNA sequencing data. The basics in biological systems are covered so learners have a foundational understanding of DNA, genomics, and DNA sequencing. Hands-on learning of data science tools is available in many courses as well, where learners use Python, R Programming, and more to analyze real genomes and DNA sequencing datasets.‎

    Computational biology sits at the intersection of machine learning and life science, so if you possess skills in computer science and any of the various disciplines of biology, you’re ready to start learning computational biology. Having a working understanding of biology, pharmacology, and genetics can help you gain a foothold in learning computational biology, and the deeper your knowledge of those fields, the better off you’ll be in your studies. You can also benefit from a background in coding and computer programming, especially if you have experience using discrete mathematics for research and data analysis. An understanding of statistics can also give you an advantage in studying computational biology because you can apply the principles of statistics and data analysis to problem-solving within scientific disciplines.‎

    Since computational biology—also known as bioinformatics—is a scientific discipline that relies on the analysis of large amounts of data, people with analytical natures or backgrounds in statistics are well-suited for careers in this area. Individuals who are passionate about life science and want to apply technology to studying its various fields will enjoy jobs in computational biology. Computer programmers who have an interest in biology or genetics can combine their skills in building data structures with their passion for bioinformatics. Whether you want to work in academic research or for a medical corporation, you can put your scientific and computational knowledge to work in a career in computational biology.‎

    Computational biology might be the right field for you if you’re interested in biology and genetics beyond family trees and the insights from DNA test kits ordered online. If you have the desire to help develop the next revolutionary prescription or a passion to use data to help solve scientific issues, learning computational biology could be a good fit for you. You can take the skills in data analysis and computer programming that you learn studying computational biology to conduct research that helps lead to scientific breakthroughs. From pharmaceutical studies to academic research, learning computational biology offers rewarding opportunities for those who want to combine computer skills with scientific exploration.‎

    Online Computational Biology courses offer a convenient and flexible way to enhance your knowledge or learn new Computational Biology skills. Choose from a wide range of Computational Biology courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Computational Biology, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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